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Record W4214779737

A qualitative study investigating research priorities and investigative capacity in sports-focused chiropractic research, part 1 - identifying research priorities to inform a Delphi study.

2021· article· en· W4214779737 on OpenAlexaffabout
Alexander Dennis Lee, Lara deGraauw, Bradley J. Muir, Melissa Belchos, Kaitlyn Szabo, Christopher DeGraauw, Scott Howitt

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticQualitative researchDelphi methodPrioritizationResearch developmentSports scienceResearch methodologyLibrary sciencePopulationSociologyPolitical scienceMedicineSocial scienceAlternative medicineManagement scienceComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: To identify sports-focused research priorities to inform the development of a research agenda for sports chiropractors. METHODS: A qualitative description study was conducted using semi-structured interviews with 20 sports chiropractic researchers from 8 different countries and focus group interviews with 12 sports chiropractic leaders from Canada. RESULTS: 150 research priorities were identified, and three main themes emerged: area of research, research actions, and research methodology. Six areas of research were identified: basic science and mechanism research, clinical research, health services research, population health, specific conditions and topics in sport, and chiropractic research in sport. Collaboration in research and contributing to the broader sports research effort were two subthemes identified as research actions, and the remaining codes were related to research methodology. CONCLUSIONS: The research priorities identified can be utilized to plan future research prioritization studies to inform a research agenda for the sports chiropractic field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.175
metaresearch head score (Gemma)0.139
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1750.139
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.014
Science and technology studies0.0050.008
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.798
GPT teacher head0.583
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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